Typically, a network camera is required to be able to provide both full and low image resolution at full field of view at the request of the user. Conventionally, the low resolution image is produced from the full resolution image received from the sensor by first converting the raw image from its Bayer array format as produced by the sensor where only one of the three color components R, G, B is available for each pixel while the two other color components are entirely missing, into a different data format via demosaicing where each pixel has a complete color representation, and only then interpolating these pixels to produce a reduced resolution image.
A demosaicing algorithm is a digital image process used to interpolate a complete image from the partial raw data received from a color-filtered image sensor (via a color filter array). A typical way the pixel filters are arranged is to alternating values of Red (R) and Green (G) for odd rows and alternating values of Green (G) and Blue (B) for even rows. Since each pixel of the sensor is behind a color filter, the output is an array of pixel values, each indicating a raw intensity of one of three primary colors. Therefore, a demosaicing process is needed to estimate the color levels for all color components for each pixel.
Moreover, the conversion from full resolution Bayer array to the final low resolution image conventionally comprises multiple related image processing steps, such as sharpening, noise filtering, and color correction. Alternatively, a low resolution Bayer array image may be produced by the image sensor itself if it is equipped with means of skipping certain rows and columns, or binning the values of certain rows and columns when reading out the image. However, image distortion in the low resolution images produced from such skipped or binned Bayer arrays is higher than in the interpolated images produced from the full resolution Bayer arrays after the demosaicing and other image processing steps as described above.